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CRC - KE38364

Statistical Modeling and Machine Learning for Molecular Biology

active, Most Current
Organization: CRC
Publication Date: 6 January 2017
Status: active
Page Count: 281
scope:

Molecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The book is devoted to teaching the statistical and computational techniques molecular biologists need to analyze their data. It explains the big-picture concepts in data analysis using a wide variety of real-world molecular biological examples such as eQTLs, ortholog identification, motif finding, inference of population structure, protein fold prediction and many more. The book takes a pragmatic approach, focusing on techniques that are based on elegant mathematics yet are the simplest to explain to scientists with little background in computers and statistics.

Document History

KE38364
January 6, 2017
Statistical Modeling and Machine Learning for Molecular Biology
Molecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The book is devoted to teaching the statistical and...
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